Perform data wrangling on OpenStreetMap data of a portion of Boston, and analyze the same using MongoDB

Data analysis in R looking at traffic summons/parking citation frequency

This contains an exploratory analysis about the link between natural events and climate change.

Used to migrate upis files to relational database

Data wrangling of Census of Agriculture data (1981-2016) from Statistics Canada

Data wrangling project with AXEM data

project from web scrapping an ecommerce website product reviews (user required) till deployment of the model to local machine can be stored using MongoDb And deployment of same on cloud platform like Heroku, Azure.

Project 4 of the Udacity Data Analyst Nanodegree Program. Data Wrangling of tweets from three different sources, with different file extensions.

Final Project

Use Python to perform Data Wrangling (gathering, assessing, cleaning) of WeRateDogs Twitter account & archive, followed by storing, analyzing and visualizing the wrangled data.

Udacity Data Analyst Nanodegree - Project IV

Prediction of future electric vehicle mileage and assessment of required infrastructure.

R package to accompany the "Introduction to Statistics and Data Science Using R" textbook

The dataset I wrangled (and analysed and visualized) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog.

An analysis of European soccer/football from 2008 to 2016 using a dataset from Kaggle. I employ different data wrangling techniques to clean and filter the data using Python and Jupyter notebook.

This project to implementing statistical inference techniques using R language.

IBS 519 Fall 2022 - MHiggins Guest Lectures

This project was a POC to determine the pricing strategy for a product using Conjoint Analysis. This is a survey-based statistical technique used in quantitative market research to determine how people value different features of a product. It helps capture the relative preference of a user over different product features.

The objective of this project is to demonstrate Data cleaning skills.

Prediction of falcon9's landing outcome showcased through a dashboard